Digital health implementations and investments continue to expand. As the reliance on digital health increases, it is imperative to implement technologies with inclusive and accessible approaches. A ...conceptual model can be used to guide equity-focused digital health implementations to improve suitability and uptake in diverse populations. The objective of this study is expand an implementation model with recommendations on the equitable implementation of new digital health technologies. The Digital Health Equity-Focused Implementation Research (DH-EquIR) conceptual model was developed based on a rigorous review of digital health implementation and health equity literature. The Equity-Focused Implementation Research for Health Programs (EquIR) model was used as a starting point and merged with digital equity and digital health implementation models. Existing theoretical frameworks and models were appraised as well as individual equity-sensitive implementation studies. Patient and program-related concepts related to digital equity, digital health implementation, and assessment of social/digital determinants of health were included. Sixty-two articles were analyzed to inform the adaption of the EquIR model for digital health. These articles included digital health equity models and frameworks, digital health implementation models and frameworks, research articles, guidelines, and concept analyses. Concepts were organized into EquIR conceptual groupings, including population health status, planning the program, designing the program, implementing the program, and equity-focused implementation outcomes. The adapted DH-EquIR conceptual model diagram was created as well as detailed tables displaying related equity concepts, evidence gaps in source articles, and analysis of existing equity-related models and tools. The DH-EquIR model serves to guide digital health developers and implementation specialists to promote the inclusion of health-equity planning in every phase of implementation. In addition, it can assist researchers and product developers to avoid repeating the mistakes that have led to inequities in the implementation of digital health across populations.
Overprescribing of antibiotics for acute respiratory infections (ARIs) remains a major issue in outpatient settings. Use of clinical prediction rules (CPRs) can reduce inappropriate antibiotic ...prescribing but they remain underutilized by physicians and advanced practice providers. A registered nurse (RN)-led model of an electronic health record-integrated CPR (iCPR) for low-acuity ARIs may be an effective alternative to address the barriers to a physician-driven model.
Following qualitative usability testing, we will conduct a stepped-wedge practice-level cluster randomized controlled trial (RCT) examining the effect of iCPR-guided RN care for low acuity patients with ARI. The primary hypothesis to be tested is: Implementation of RN-led iCPR tools will reduce antibiotic prescribing across diverse primary care settings. Specifically, this study aims to: (1) determine the impact of iCPRs on rapid strep test and chest x-ray ordering and antibiotic prescribing rates when used by RNs; (2) examine resource use patterns and cost-effectiveness of RN visits across diverse clinical settings; (3) determine the impact of iCPR-guided care on patient satisfaction; and (4) ascertain the effect of the intervention on RN and physician burnout.
This study represents an innovative approach to using an iCPR model led by RNs and specifically designed to address inappropriate antibiotic prescribing. This study has the potential to provide guidance on the effectiveness of delegating care of low-acuity patients with ARIs to RNs to increase use of iCPRs and reduce antibiotic overprescribing for ARIs in outpatient settings.
ClinicalTrials.gov Identifier: NCT04255303, Registered February 5 2020, https://clinicaltrials.gov/ct2/show/NCT04255303 .
The COVID-19 pandemic has boosted digital health utilization, raising concerns about increased physicians' after-hours clinical work ("work-outside-work"). The surge in patients' digital messages and ...additional time spent on work-outside-work by telemedicine providers underscores the need to evaluate the connection between digital health utilization and physicians' after-hours commitments. We examined the impact on physicians' workload from two types of digital demands - patients' messages requesting medical advice (PMARs) sent to physicians' inbox (inbasket), and telemedicine. Our study included 1716 ambulatory-care physicians in New York City regularly practicing between November 2022 and March 2023. Regression analyses assessed primary and interaction effects of (PMARs) and telemedicine on work-outside-work. The study revealed a significant effect of PMARs on physicians' work-outside-work and that this relationship is moderated by physicians' specialties. Non-primary care physicians or specialists experienced a more pronounced effect than their primary care peers. Analysis of their telemedicine load revealed that primary care physicians received fewer PMARs and spent less time in work-outside-work with more telemedicine. Specialists faced increased PMARs and did more work-outside-work as telemedicine visits increased which could be due to the difference in patient panels. Reducing PMAR volumes and efficient inbasket management strategies needed to reduce physicians' work-outside-work. Policymakers need to be cognizant of potential disruptions in physicians carefully balanced workload caused by the digital health services.
Observational studies suggest that there are differences in adherence to antihypertensive medications in different classes. Our objective was to quantify the association between antihypertensive drug ...class and adherence in clinical settings.
Studies were identified through a systematic search of English-language articles published from the inception of computerized databases until February 1, 2009. Studies were included if they measured adherence to antihypertensives using medication refill data and contained sufficient data to calculate a measure of relative risk of adherence and its variance. An inverse-variance-weighted random-effects model was used to pool results. Hazard ratios (HRs) and odds ratios were pooled separately, and HRs were selected as the primary outcome. Seventeen studies met inclusion criteria. The pooled mean adherence by drug class ranged from 28% for β-blockers to 65% for angiotensin II receptor blockers. There was better adherence to angiotensin II receptor blockers compared with angiotensin-converting enzyme inhibitors (HR, 1.33; 95% confidence interval, 1.13 to 1.57), calcium channel blockers (HR, 1.57; 95% confidence interval, 1.38 to 1.79), diuretics (HR, 1.95; 95% confidence interval, 1.73 to 2.20), and β-blockers (HR, 2.09; 95% confidence interval, 1.14 to 3.85). Conversely, there was lower adherence to diuretics compared with the other drug classes. The same pattern was present when studies that used odds ratios were pooled. After publication bias was accounted for, there were no longer significant differences in adherence between angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors or between diuretics and β-blockers.
In clinical settings, there are important differences in adherence to antihypertensives in separate classes, with lowest adherence to diuretics and β-blockers and highest adherence to angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors. However, adherence was suboptimal regardless of drug class.
Effective communication of risks and benefits to patients is critical for shared decision making.
To review the comparative effectiveness of methods of communicating probabilistic information to ...patients that maximize their cognitive and behavioral outcomes.
PubMed (1966 to March 2014) and CINAHL, EMBASE, and the Cochrane Central Register of Controlled Trials (1966 to December 2011) using several keywords and structured terms.
Prospective or cross-sectional studies that recruited patients or healthy volunteers and compared any method of communicating probabilistic information with another method.
Two independent reviewers extracted study characteristics and assessed risk of bias.
Eighty-four articles, representing 91 unique studies, evaluated various methods of numerical and visual risk display across several risk scenarios and with diverse outcome measures. Studies showed that visual aids (icon arrays and bar graphs) improved patients' understanding and satisfaction. Presentations including absolute risk reductions were better than those including relative risk reductions for maximizing accuracy and seemed less likely than presentations with relative risk reductions to influence decisions to accept therapy. The presentation of numbers needed to treat reduced understanding. Comparative effects of presentations of frequencies (such as 1 in 5) versus event rates (percentages, such as 20%) were inconclusive.
Most studies were small and highly variable in terms of setting, context, and methods of administering interventions.
Visual aids and absolute risk formats can improve patients' understanding of probabilistic information, whereas numbers needed to treat can lessen their understanding. Due to study heterogeneity, the superiority of any single method for conveying probabilistic information is not established, but there are several good options to help clinicians communicate with patients.
None.
Among individuals without diabetes, elevated hemoglobin A1c (HbA1c) has been associated with increased morbidity and mortality, but the literature is sparse regarding the prognostic importance of low ...HbA1c.
National Health and Nutrition Examination Survey III (NHANES III) participants, 20 years and older, were followed up to 12 years (median follow-up, 8.8 years) for all-cause mortality. Cox proportional hazards regression was used to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the association between HbA1c levels and all-cause mortality for 14 099 participants without diabetes. There were 1825 deaths during the follow-up period. Participants with a low HbA1c (<4.0%) had the highest levels of mean red blood cell volume, ferritin, and liver enzymes and the lowest levels of mean total cholesterol and diastolic blood pressure compared with their counterparts with HbA1c levels between 4.0% and 6.4%. An HbA1c <4.0% versus 5.0% to 5.4% was associated with an increased risk of all-cause mortality (HR, 3.73; 95% CI, 1.45 to 9.63) after adjustment for age, race-ethnicity, and sex. This association was attenuated but remained statistically significant after further multivariable adjustment for lifestyle, cardiovascular factors, metabolic factors, red blood cell indices, iron storage indices, and liver function indices (HR, 2.90; 95% CI, 1.25 to 6.76).
In this nationally representative cohort, low HbA1c was associated with increased all-cause mortality among US adults without diabetes. Additional research is needed to confirm these results and identify potential mechanisms that may be underlying this association.
Statins reduce the risk of coronary heart disease (CHD) in individuals with a history of CHD or risk equivalents. A 10-year CHD risk >20% is considered a risk equivalent but is frequently not ...detected. Statin use and low-density lipoprotein cholesterol (LDL-C) control were examined among participants with CHD or risk equivalents in the nationwide Reasons for Geographic and Racial Differences in Stroke study (n = 8812).
Participants were categorized into 4 mutually exclusive groups: (1) history of CHD (n = 4025); (2) no history of CHD but with a history of stroke and/or abdominal aortic aneurysm (AAA) (n = 946); (3) no history of CHD or stroke/AAA but with diabetes mellitus (n = 3134); or (4) no history of the conditions in (1) through (3) but with 10-year Framingham CHD risk score (FRS) >20% calculated using the third Adult Treatment Panel point scoring system (n = 707).
Statins were used by 58.4% of those in the CHD group and 41.7%, 40.4% and 20.1% of those in the stroke/AAA, diabetes mellitus and FRS >20% groups, respectively. Among those taking statins, 65.1% had LDL-C <100 mg/dL, with no difference between the CHD, stroke/AAA, or diabetes mellitus groups. However, compared with those in the CHD group, LDL-C <100 mg/dL was less common among participants in the FRS >20% group (multivariable adjusted prevalence ratio: 0.72; 95% confidence interval: 0.62-0.85). Results were similar using the 2013 American College of Cardiology/American Heart Association cholesterol treatment guideline.
These data suggest that many people with high CHD risk, especially those with an FRS >20%, do not receive guideline-concordant lipid-lowering therapy and do not achieve an LDL-C <100 mg/dL.
To determine diabetic patients' knowledge and beliefs about the disease and medications that could hinder optimal disease management.
A cross-sectional survey of 151 type 2 diabetic patients ...characterizing diabetes knowledge and beliefs about the disease and medications was conducted.
Mean diabetes duration was 13 years. Over half of the patients (56%) believed that normal glucose is <or=200 mg/dl, 54% reported being able to feel when blood glucose levels are high, 36% thought that they will not always have diabetes, 29% thought that their doctor will cure them of diabetes, one in four (23%) said there is no need to take diabetes medications when glucose levels are normal, and 12% believed they have diabetes only when glucose levels are high.
Diabetes knowledge and beliefs inconsistent with a chronic disease model of diabetes were prevalent in this sample. Suboptimal knowledge and beliefs are potentially modifiable and are logical targets for educational interventions to improve diabetes self-management.
The COVID-19 pandemic accelerated the adoption of remote patient monitoring technology, which offers exciting opportunities for expanded connected care at a distance. However, while the mode of ...clinicians' interactions with patients and their health data has transformed, the larger framework of how we deliver care is still driven by a model of episodic care that does not facilitate this new frontier. Fully realizing a transformation to a system of continuous connected care augmented by remote monitoring technology will require a shift in clinicians' and health systems' approach to care delivery technology and its associated data volume and complexity. In this article, we present a solution that organizes and optimizes the interaction of automated technologies with human oversight, allowing for the maximal use of data-rich tools while preserving the pieces of medical care considered uniquely human. We review implications of this "augmented continuous connected care" model of remote patient monitoring for clinical practice and offer human-centered design-informed next steps to encourage innovation around these important issues.
Abstract Lifestyle behavior changes can prevent progression of prediabetes to diabetes but providers often are not able to effectively counsel about preventive lifestyle changes. We developed and ...pilot tested the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) program to enhance primary care providers' counseling about behavior change for patients with prediabetes. Primary care providers in two urban academic practices and their patients with prediabetes were recruited to participate in the ADAPT study, an unblinded randomized pragmatic trial to test the effectiveness of the ADAPT program, including a streamlined electronic medical record-based goal setting tool. Providers were randomized to intervention or control arms; eligible patients whose providers were in the intervention arm received the ADAPT program. Physical activity (the primary outcome) was measured using pedometers, and data were gathered about patients' diet, weight and glycemic control. A total of 54 patients were randomized and analyzed as part of the 6-month ADAPT study (2010–2012, New York, NY). Those in the intervention group showed an increase total daily steps compared to those in the control group (+ 1418 vs − 598, p = 0.007) at 6 months. There was also a trend towards weight loss in the intervention compared to the control group (− 1.0 lbs. vs. 3.0 lbs., p = 0.11), although no change in glycemic control. The ADAPT study is among the first to use standard electronic medical record tools to embed goal setting into realistic primary care workflows and to demonstrate a significant improvement in prediabetes patients' physical activity.
PDF
